The present invention generally relates to the field of computational biology, and more particularly relates to stable gene analysis of transcriptome sequencing data.
Transcriptome data, including messenger ribonucleic acid (mRNA) data, may arise from genes, and more specifically from gene transcripts. A gene may have multiple differently spliced transcripts that give rise to mRNAs, and mRNAs may also arise from other regions on the genome. Sequencing technologies may provide data for a wide range of biological applications, and are powerful tools for investigating and understanding mRNA expression profiles. There is no limit on the number of mRNAs that may be surveyed by sequencing. Sequencing may not be target specific, so the genes that are examined do not have to be pre-selected, providing a wide dynamic range of data and also allowing the possibility of discovering new sequence variants and transcripts.
Various sequencing platforms may be used to perform mRNA sequencing and to produce mRNA sequencing datasets, each dataset corresponding to an assay of a particular sample. Such mRNA sequencing technologies may be high-throughput and produce relatively large amounts of sequence data. The size of an mRNA sequencing dataset may require the use of various computational techniques to make accurate and meaningful inferences regarding sequenced mRNAs from the dataset. In addition, datasets from different assays (which may be from the same sample at different points in time or from different samples) may also need to be compared. Analyzing data regarding relatively large numbers of mRNAs based on their activity, or expression, levels across different assays may be a complex process.